The importance of making accurate estimates to control marine litter (2025)

Pollution by marine litter of anthropogenic origin—that comes from human activity—is currently one of the biggest environmental concerns given its increasing magnitude, especially due to the considerable amount of plastics present in the marine environment.

A study carried out by the University of Malaga and the Oceanographic Center of the Balearic Islands (COB-IEO/CSIC) and published in the Marine Pollution Bulletin highlights the importance of making accurate estimates of the amount of marine litter to face this challenge, which not only affects the scientific community but also the general public.

"The Mediterranean Sea, characterized by being a semi-enclosed basin with intense demographic pressure, is one of the world's most vulnerable regions with respect to this type of pollution, with direct effects on its very high biodiversity," says Javier Soto-Navarro, researcher of the Department of Applied Physics II of the University of Malaga, one of the authors of this study.

Inadequate results

Together with the scientist of the Oceanographic Center of the Balearic Islands of the Spanish Institute of Oceanography (COB-IEO/CSIC) Gabriel Jordá, they have found that the monitoring strategies commonly implemented in the observational campaigns undertaken so far are inadequate for obtaining average values of marine litter concentration within an acceptable uncertainty range (20%–30%).

"It is, without a doubt, a very complex task, as it requires scarce and very expensive resources and, additionally, it depends on factors that are out of researchers' control, such as meteorological factors," explains Soto-Navarro.

Experts point out that uncertainty in the results obtained can be largely attributed to the sampling techniques and strategies employed.

Simulation experiments

This study led by the University of Malaga has analyzed the spatial and temporal requirements for marine litter sampling in the Mediterranean Sea. For this purpose, experiments have been carried out with a simulated observation system (OSSE), which is based on using synthetic or simulated reality.

To obtain this synthetic reality, a high-resolution numerical modeling system has been used that simulates the circulation of the basin and the dispersion of litter in it. In this way, according to the UMA scientist, a representation of the distribution and variability of marine litter concentrations is achieved as realistically as possible.

"The different sampling strategies are evaluated on this simulated reality, performing a series of virtual experiments. For example, what values of the temporal average of concentration we obtain if we measure over a one-month period, with a daily sampling frequency. By varying the period and frequency, the temporal average errors are estimated. As for spatial averages, we proceed in a similar way, but studying the variability of the results based on the target area at a specific moment," he clarifies.

"Since this is a simulated reality, we have all the necessary information to estimate and compare the errors of plastic concentration averages, based on the strategy used in the different experiments. This analysis enables the identification of the most appropriate sampling strategies," explains Soto-Navarro.

The most appropriate sampling strategies

Therefore, it has been shown that the magnitude of errors in the average concentration, both spatial and temporal, can be quantified based on the strategy used. Specifically, with regard to temporal averages, it is evident that it is much more efficient to extend campaigns over time than to increase the number of observations in shorter campaigns.

As for spatial averages, on the other hand, it is determined that characterizing synoptically, in a schematic way, the entire basin or even smaller sub-basins would require a considerable increase in the number of observations.

"It is necessary to rethink the strategies used so far to monitor marine litter. With the same sampling strategy, it is feasible to achieve significantly more accurate results by better planning the campaigns, coordinating the different groups involved and establishing standardized protocols to integrate the measures made by different teams into a unified database," concludes Soto-Navarro.